Delivering this course:

Gad is an applied researcher, currently consulting Gett. Gad has served in an IDF technological unit experting in data analysis and AI

Hands-on Machine Learning and Artificial Intelligence

Jump into the fascinating world of artificial intelligence

What do cancer detection, sentiment analysis, image recognition, machine translation and playing atari games have in common? These are all complex real-world tasks, and the goal of artificial intelligence (AI) is to tackle these with powerful mathematical and programmatic tools. In this course, you will learn the foundational principles that enables machines to make autonomous decisions and practice implementing some of these systems. The main goal of the course is to equip you with the tools to tackle new AI problems you might encounter in your field of interest.

Objectives

Key elements you will encounter:

The concept of loss functions and gradient descent optimizer

Build machine learning models based on domain knowledge

Visualize and explore datasets using python

Extract informative features and transform them to fit into specific algorithm

Implement NLP and text analysis tools to analyze sentiment of tweets

Get familiar with the theory and implementations of several learning algorithms: ANN, XGB, Random Forest, Logistic Regression

Intended Audience

This course is intended for individuals interested in machine learning and AI who would like to bootstrap their skills and knowledge to a level in which they will be able to start acquiring significant experience in applying machine learning algorithms to real life projects

Prerequisites

We recommend that attendees of this course have the following prerequisites: